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Regime Switching Volatility Calibration by the Baum-Welch Method

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  • Sovan Mitra

Abstract

Regime switching volatility models provide a tractable method of modelling stochastic volatility. Currently the most popular method of regime switching calibration is the Hamilton filter. We propose using the Baum-Welch algorithm, an established technique from Engineering, to calibrate regime switching models instead. We demonstrate the Baum-Welch algorithm and discuss the significant advantages that it provides compared to the Hamilton filter. We provide computational results of calibrating the Baum-Welch filter to S&P 500 data and validate its performance in and out of sample.

Suggested Citation

  • Sovan Mitra, 2009. "Regime Switching Volatility Calibration by the Baum-Welch Method," Papers 0904.1500, arXiv.org.
    • Handle: RePEc:arx:papers:0904.1500
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    File URL: http://arxiv.org/pdf/0904.1500
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    Cited by:

    1. Mesias Alfeus, 2019. "Stochastic Modelling of New Phenomena in Financial Markets," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2019.
    2. Mesias Alfeus & Ludger Overbeck & Erik Schlögl, 2019. "Regime switching rough Heston model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(5), pages 538-552, May.
    3. repec:uts:finphd:41 is not listed on IDEAS
    4. Mesias Alfeus & Ludger Overbeck, 2018. "Regime Switching Rough Heston Model," Research Paper Series 387, Quantitative Finance Research Centre, University of Technology, Sydney.

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